Safety versus Compensation for Professional Athletes Who Face the Prospect of Career-Ending Injuries: An Economic Risk Analysis
Bibliographic record
Abstract
The National Football League and National Hockey League have instituted several rule changes, equipment improvements and medical protocols in response to the frequency of serious career-ending injuries. These two professional leagues and others have litigated lawsuits by former players who have sought financial compensation. This paper constructs a simple economic model of a risk averse athlete who faces the uncertain prospect of a career-ending injury. Improving the athlete’s welfare can be accomplished by reducing the probability of a serious injury or providing increased compensation in the event of such an injury. The net marginal preference for safety is high in sports with moderate to high probabilities of serious injury. Compensation plans are favored in sports with moderate to low probabilities. Significant increases in player salaries have little effect on a players net marginal preference for safety. These results are robust to constant or decreasing absolute risk aversion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".